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      The genome of the emerging barley pathogen Ramularia collo- cygni

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          Abstract

          Background

          Ramularia collo- cygni is a newly important, foliar fungal pathogen of barley that causes the disease Ramularia leaf spot. The fungus exhibits a prolonged endophytic growth stage before switching life habit to become an aggressive, necrotrophic pathogen that causes significant losses to green leaf area and hence grain yield and quality.

          Results

          The R. collo- cygni genome was sequenced using a combination of Illumina and Roche 454 technologies. The draft assembly of 30.3 Mb contained 11,617 predicted gene models. Our phylogenomic analysis confirmed the classification of this ascomycete fungus within the family Mycosphaerellaceae, order Capnodiales of the class Dothideomycetes. A predicted secretome comprising 1053 proteins included redox-related enzymes and carbohydrate-modifying enzymes and proteases. The relative paucity of plant cell wall degrading enzyme genes may be associated with the stealth pathogenesis characteristic of plant pathogens from the Mycosphaerellaceae. A large number of genes associated with secondary metabolite production, including homologs of toxin biosynthesis genes found in other Dothideomycete plant pathogens, were identified.

          Conclusions

          The genome sequence of R. collo- cygni provides a framework for understanding the genetic basis of pathogenesis in this important emerging pathogen. The reduced complement of carbohydrate-degrading enzyme genes is likely to reflect a strategy to avoid detection by host defences during its prolonged asymptomatic growth. Of particular interest will be the analysis of R. collo- cygni gene expression during interactions with the host barley, to understand what triggers this fungus to switch from being a benign endophyte to an aggressive necrotroph.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-016-2928-3) contains supplementary material, which is available to authorized users.

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          Most cited references111

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          MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

          K Katoh (2002)
          A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
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            Cluster analysis and display of genome-wide expression patterns.

            A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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              RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

              RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak
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                Author and article information

                Contributors
                +44(0) 131 535 4212 , graham.mcgrann@sruc.ac.uk
                ambrose.adongabo@rothamsted.ac.uk
                elisabet.sjokvist@sruc.ac.uk
                urmi.trivedi@ed.ac.uk
                francois.dussart@sruc.ac.uk
                maciej.kaczmarek@forestry.gsi.gov.uk
                ashleigh.mackenzie@sruc.ac.uk
                James.Fountaine@SYNGENTA.com
                jeanette.taylor@sruc.ac.uk
                linda.paterson@sruc.ac.uk
                kalina.gorniak@sruc.ac.uk
                fiona.burnett@sruc.ac.uk
                kostya.kanyuka@sruc.ac.uk
                kim.hammond-kosack@rothamsted.ac.uk
                jason.rudd@rothasted.ac.uk
                mark.blaxter@ed.ac.uk
                neil.havis@sruc.ac.uk
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                9 August 2016
                9 August 2016
                2016
                : 17
                : 584
                Affiliations
                [1 ]Crop Protection Team, Crop and Soil Systems Group, SRUC, West Mains Road, Edinburgh, EH9 3JG UK
                [2 ]Department of Computational and Systems Biology, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ UK
                [3 ]Department of Plant Biology and Crop Science, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ UK
                [4 ]Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3TF UK
                [5 ]Edinburgh Genomics, The University of Edinburgh, Edinburgh, EH9 3JT UK
                [6 ]Present address: Forest Research, Alice Holt Lodge, Farnham, Surrey GU10 4LH UK
                [7 ]Present address: Syngenta, Jealott’s Hill International Research Centre, Bracknell, Berkshire RG42 6EY UK
                Article
                2928
                10.1186/s12864-016-2928-3
                4979122
                27506390
                5d48cd31-3840-4f34-9e54-b114f936bcd8
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 9 November 2015
                : 12 July 2016
                Funding
                Funded by: RESAS
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/J/00426X/1
                Award ID: BB/J004243/1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/http://dx.doi.org/10.13039/100007398, Strategiske Forskningsråd;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000270, Natural Environment Research Council;
                Award ID: R8/H10/56
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Genetics
                ramularia leaf spot,dothideomycetes,rubellin toxin,endophyte,necrotroph,whole genome sequencing

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